Correlation Between Alumil Aluminium and Dow Jones
Can any of the company-specific risk be diversified away by investing in both Alumil Aluminium and Dow Jones at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Alumil Aluminium and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Alumil Aluminium Industry and Dow Jones Industrial, you can compare the effects of market volatilities on Alumil Aluminium and Dow Jones and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Alumil Aluminium with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Alumil Aluminium and Dow Jones.
Diversification Opportunities for Alumil Aluminium and Dow Jones
0.83 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Alumil and Dow is 0.83. Overlapping area represents the amount of risk that can be diversified away by holding Alumil Aluminium Industry and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial and Alumil Aluminium is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Alumil Aluminium Industry are associated (or correlated) with Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of Alumil Aluminium i.e., Alumil Aluminium and Dow Jones go up and down completely randomly.
Pair Corralation between Alumil Aluminium and Dow Jones
Assuming the 90 days trading horizon Alumil Aluminium Industry is expected to generate 2.36 times more return on investment than Dow Jones. However, Alumil Aluminium is 2.36 times more volatile than Dow Jones Industrial. It trades about 0.4 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.34 per unit of risk. If you would invest 327.00 in Alumil Aluminium Industry on September 2, 2024 and sell it today you would earn a total of 69.00 from holding Alumil Aluminium Industry or generate 21.1% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 95.45% |
Values | Daily Returns |
Alumil Aluminium Industry vs. Dow Jones Industrial
Performance |
Timeline |
Alumil Aluminium and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
Alumil Aluminium Industry
Pair trading matchups for Alumil Aluminium
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with Alumil Aluminium and Dow Jones
The main advantage of trading using opposite Alumil Aluminium and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Alumil Aluminium position performs unexpectedly, Dow Jones can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Dow Jones will offset losses from the drop in Dow Jones' long position.Alumil Aluminium vs. Hellenic Petroleum SA | Alumil Aluminium vs. Mytilineos SA | Alumil Aluminium vs. GEK TERNA Holdings | Alumil Aluminium vs. Aegean Airlines SA |
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Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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